AWS for Software Companies Podcast

AWS's Shahid Mohammed and Darktrace's Michael Beck discuss how generative AI innovations are transforming cybersecurity by both enhancing defences and introducing new, sophisticated threat management strategies.Topics Include:Shahid Mohammed introduces himself as a lead solution architect at AWS.Mike Beck is Global Chief Information Security Officer at Darktrace.Darktrace specializes in AI-driven cybersecurity solutions for digital environments.Darktrace secures multiple digital data pots: email, network, cloud, SaaS, and endpoint.The conversation focuses on innovation in cybersecurity through AI.Mike emphasizes the benefits of Gen AI despite its security risks.Gen AI enables more complex, targeted attacks against organizations.Attackers use Gen AI to tailor attacks through phishing and deepfakes.Gen AI increases phishing complexity by eliminating common detection cues.Data privacy risks arise when large models process sensitive business data.Businesses must be mindful of AI’s impact on data sovereignty and security.Shahid compares the cybersecurity space to an arms race due to Gen AI.Mike stresses the importance of choosing the right AI for each task.Darktrace uses unsupervised machine learning and Gen AI together for defense.AI is essential for scaling cybersecurity efforts given today's threat complexity.Darktrace relies on AWS cloud for compute power, scaling, and innovation.AWS infrastructure helps accelerate Darktrace's R&D and operations securely.Security leaders should implement Gen AI policies and training.Mike advises technical controls and monitoring for safe Gen AI use.Gen AI is here to stay, but businesses must handle its security implications carefully.Participants:Michael Beck – Global CISO - DarktraceShahid Mohammed – Solution Architect Manager – Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Daryl Martis of Salesforce and Rashna Chadha of AWS share how Amazon Bedrock integrates with Salesforce to enhance AI applications, highlighting the partnership's strategic benefits, AI model customization, and secure deployment options.Topics Include:Introduction to Amazon Bedrock and Salesforce partnership.Overview of Amazon Bedrock as an API-based generative AI service.The strategic collaboration between AWS and Salesforce.Salesforce Data Cloud and its integration with Amazon Bedrock.Overview of Salesforce Einstein and its use of Amazon SageMaker.Recent AI launches between Salesforce and AWS, including Slack AI and MuleSoft.Use cases of AI services like Amazon Textract within Salesforce.Bringing Your Own Large Language Model (BYO LLM) with Bedrock.Foundation models offered by Amazon Bedrock (Anthropic, Cohere, Llama).Overview of security, privacy, and compliance in Bedrock AI services.Salesforce Data Cloud’s unified customer data and real-time AI capabilities.Bedrock’s support for custom AI model evaluation and metrics.Consumption models in Bedrock: on-demand vs. provision throughput.Bedrock’s agent capabilities for real-world applications like scheduling.Demo of using Amazon Bedrock models within Salesforce.Participants:Daryl Martis – Director of Product Management, Einstein AI - SalesforceRashna Chadha – AI/ML Specialist – Principal Solution Architect – Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ashish Arora, Head of Engineering & Machine Learning, Product Analytics at Autodesk, shares how personalized AI-powered experiences and real-time data can drive product adoption, featuring insights into Autodesk’s transformation journey, leveraging machine learning, and delivering actionable recommendations to millions of users.Topics Include:Real-time data description and examplesLeveraging AWS for real time and generative AI servicesAutodesk’s journey leveraging AWS to transform architecture and deliver personalized insightsOverview of Autodesk and product portfolioUtilizing data gathered for customersPersonalized data-driven insights for customers on Autocad and other productsDescriptive insights: providing usage data for customersPrescriptive insights: Making recommendations to customers based on their workflowsPredictive insights: Using ML to recommend products and featuresAutodesk processes 100+ billion events across all products, delivered 350+ million insights to customers, served to 3.5 million customersExample walkthrough – RachaelArchitecture of Autodesk data and insight processLeveraging LLMs – Sagemaker and BedrockBringing it altogetherSession wrap upParticipants:Ashish Arora – Head of Engineering & ML, Product Analytics - AutodeskBrian Slater – Principal Solutions Architect – Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

A panel discussion on presenting on security and data to Boards of Directors, focusing on metrics, ROI, generative AI, securing intellectual property, and strategic board engagement.Topics Include:What security metrics are most valuable for Board of DirectorsArticulating ROI of security programQuantifying benefits of security programSales enablement of the security teamDriving efficiencies within the business with generative AI and moreQuantifying business and template-based reporting to Boards with Diligent softwareLeveraging consultants and 3rd parties to leverage messages to Board of DirectorsManaging and communicating data posture and risk managementWorking with data leadership, securing intellectual propertyChallenges of labelling dataEducating boards on software architecture principles and generative AIHigh focus and techniques for securing IPEnrolling Boards with generative AI use cases and innovationCreating communities of excellenceGamifying security and generative AI to increase internal knowledgeQ&A 1: Taking action on a summarized documentQ&A 2: Mental model for evaluative SaaS partnersQ&A 3: Using the board to influence budgetary decisionsSession wrap upParticipants:Satheesh Ravala - Chief Technology Officer, DiligentJosh Blackwelder – Deputy CISO, Sentinel OneRobert Huber - Chief Security Officer, Head of Tenable Research, President Tenable PublicKaren Henlsey - Principal WW Data & Generative AI Strategist, AWS

Lacework’s VP and Head of Engineering Arash Nikkar, and Product and Security Software Engineer Teddy Reed, discuss their work with generative AI and Amazon Bedrock, focusing on threat detection, chat interface improvements, and the rapid development of AI-driven solutions.Topics Include:Introducing Lacework with Arash NikkarWorking with AWS and BedrockFocusing on threat detectionLacework ingests over a trillion events each dayComposite alerts for detecting anomaliesDeveloping and improving the chat interfaceTeddy Reed talking chat interface improvementsReviewing the architectureFast engagement with generative AI / AWS BedrockThe rapid delivery with Bedrock – took 20% of expected timeBest practice – build in time to review and verify responsesMeasuring customer’s engagement and return frequency and feedbackUnderstanding customer sentiment and topic analysisAchieving 60% completed results and feedbackTransparency of source, responseEnabling assistant to have more access to data from LLMUsing AWS’ model evaluator, raising the accuracy scoresMoving everything over to Bedrock for multiple reasonsFamiliarity of AWS tools helpful for all development and security teamsAlways challenging assumptions – is chat interface the right interface?Q&A 1: Using vector database for analysis, using results as system promptQ&A 2: Approaching cost-optimization and balancing ROIQ&A 3: Using as automated remediation for findingsQ&A 4: Data source Bedrock in leveragingSession wrap upParticipants:Arash Nikkar – VP, Head of Engineering – LaceworkTeddy Reed – Product and Security Software Engineer - Lacework

Massimo Ghislandi from AWS interviews Frank Contrepois, Chief Innovation Officer of Strategic Blue and Dvir Mizrahi, Head of FinOps for WIX sharing perspectives and best practices for FinOps, implementation, challenges and future FinOps trends for software companies.Topics Include:FinOps is a new approach to managing cloud finances, bridging the gap between finance, engineering, and business stakeholdersThe implementation of FinOps can take a top-down or bottom-up approach, requiring collaboration and a common language across teamsShifting the conversation from "costs" to "investment" and "efficiency" has been an effective strategy for driving cultural changeFocusing on automation, governance, remediation, and anomaly detection can have a greater impact than just cost observabilityEducating finance teams on technical cloud concepts and vice versa is crucial for building trust and alignmentThe future of FinOps may involve expanding beyond just cloud to encompass all IT assets and aligning with a company's overall values and business objectivesPotential changes in legislation or accounting practices related to cloud could drastically impact the FinOps landscapeParticipants:Frank Contrepois – Chief Innovation Officer, Strategic BlueDvir Mizrahi – Head of Financial Engineering (FinOps), WIXMassimo Ghislandi – ISV Marketing Leader, EMEA, AWS

We feature a panel of executives from ASAPP, Glean, Smarsh, Socotra and AWS sharing essential strategies, including the role of Generative AI, trust-building, and addressing legal challenges to secure executive buy-in for transformative initiatives.Topics Include:Introductions to panelExample of ideal Executive SellerDepth of business acumen and problem solving are important skills for Executive SellersFraming a customer problem and create the argumentMaking selling to a C-Suite a team sportKeeping sellers and produce C-suite relevantRevolution and renaissance positioningTrust with the C-suite – do salesperson have a texting relationship w decision makers?How is Generative AI driving customer’s satisfaction and dissatisfaction?Data is the new oilDefining the business problem for insurance industryHelping customers reimagine business with Generative AI80% of customers report the chatbot makes them madThe data journey is the precursor to the Generative AI journeyThe top unique legal challenges with Generative AILegal now brought into early stage of sales processTurning legal concerns into an opportunityThe book “Never Split the Difference” by Christopher VossCalls to action from each panellistSession wrap-upParticipants:Daniel Rood – Senior Vice President Marketing, ASAPPAJ Tennant – Vice President Sales & Success, GleanNeva DePalma – General Council, SmarshEkine Akuiyibo – Chief Business Officer, SocotraLauren Larscheid – Sr. Sales Leader, Business Applications, AWS

Today Anthropic’s Zach Witten takes us on a deep dive into Anthropic’s cutting-edge AI models—Claude Haiku, Sonnet, and Opus—exploring their safety-first approach to generative AI and sharing essential tips for prompt engineering.Topics Include:Introductions, about Anthropic3 models: Haiku, Sonnet and OpusScaling laws for hardware, data and computeCompeting to be safest AI solutions, safety-first organizationLeader in jailbreak resistanceInterpretability features and breakthroughs for AI modelsBasics of prompt engineeringImproving prompts with ClaudeDetails matter – small changes to spelling, context will greatly improve resultsSystem prompt – role setting will improve results (i.e. “You are an expert mathematician…” for math queryBe clear and direct – use XML tags where possibleEncourage Claude to think step-by-step – answering fast comes with accuracy riskUse examples to provide additional clarity to ClaudeBonus tips for image-based prompt engineeringQ&A 1) Who wrote the meta-prompts in the cookbook?Q&A 2) Guidance for writing prompts for prompt generatorQ&A 3) Best practices for tabular and structured dataQ&A 4) Maintaining “tone” across hundreds/thousands of responsesQ&A 5) Reverse engineering a prompt

Today, Dr. Ratinder Paul Singh Ahuja of Pure Storage takes us through how his organization is leveraging Amazon Bedrock to enrich the digital experience for end users and increase returns for the company.Topics Include:IntroductionsGenerative AI activity within Pure StorageOwnership and expertise of team, role of generative AIRapid changes require dedicated team reporting to office of CTOWhere Pure Storage is investing – Productivity gains, Customer Experience, R&DVision starts with the needs of the business usersGenAI Ops – Content, Voctor databases for ingestion, query strategies & securityExample – Purchase Acquisition ProcessFeatures for a mobile experienceConfigurations and logs are getting more enhanced with generative AIDefining schema and improving large language model for more accurate responsesSecurity models and deploymentSummary and session wrap upQ&A 1) How did the team get trained to use the generative AI tools and systems?Q&A 2) How did the team reduce the hallucinations?Q&A 3) How did you decide on which foundation models to use?Q&A 4) The ROI of this particular use caseQ&A 5) Models working with poly-morphic evolving inputsSession conclusion

Federico Torreti and Tom Sly of AWS discuss how application developers can leverage Generative AI to enhance cross-app experiences, minimize custom integrations and increase the value-add of enhanced communication features.Topics Include:Federico Torreti intro: What is AWS’ vision for applicationsFocus of Machine Learning & AIAbility to build rapid prototypes, experimentationCambrian explosion of SaaS applicationsThe challenge of toggling of multiple applicationsBringing the world of disconnected appsData and focusing on the primary value for customerGenerating more content will raise number of alerts and potential of burnoutTom Sly intro: Being delighted by businessesCustomers expect personalization from businessesMore than 150,000 customers leverage AWS for communications strategyLeveraging messaging to increase customer delight2 examples: restaurant and medical needSession wrap upParticipants:Federico Torreti – Head of Product – Amazon Q, Amazon Web ServicesTom Sly - Director, Special Projects, Amazon Web Services